Transportation mode detection from smartphone data is investigated as a relevant problem
in the multi-modal transportation systems context. Neural networks are chosen as a timely …

Transportation Mode Detection (TMD) is an important task for the Intelligent Transportation
System (ITS) and Lifelog. TMD, using smartphone built-in sensors, can be a low-cost and …

The wide utilization of smartphones has provided extensive availability to Inertial
Measurement Units, providing a wide range of sensory data that can be advantageous for …

Intelligent Transportation System's main objective is to provide sustainable and optimized
means of transportation for citizens of urban centers. Identifying the travel modes used by …

The widespread utilization of smartphones has provided extensive availability to Inertial
Measurement Units, providing a wide range of sensory data that can be advantageous for …

In recent years, with the development of science and technology, people have more and
more choices for daily travel. However, assisting with various mobile intelligent services by …

Transport mode detection is a classification problem aiming to design an algorithm that can
infer the transport mode of a user given multimodal signals (GPS and/or inertial sensors). It …

Transportation mode detection (TMD), as an essential part of Intelligent Transportation
Systems, aims at analyzing human current transportation activities, and can be widely …

Understanding people's transportation modes is beneficial for empowering many intelligent
transportation systems, such as supporting urban transportation planning. Yet, current …

The advancement of sensing technologies coupled with the rapid progress in big data
analysis has ushered in a new era in intelligent transport and smart city applications. In this …